Go through the table with a loop and change values
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I have 30 columns and there are values in these columns.
2 Kommentare
Antworten (3)
Subhadeep Koley
am 12 Feb. 2020
Bearbeitet: Subhadeep Koley
am 12 Feb. 2020
ds = record ("xlsfile", "dataset.csv");
data = dataset2table(ds);
[rows, cols] = size(data);
newData = data;
for i = 1: rows
for j = 1: cols
if table2array(data(i, j)) == -9
newData(i, j) = array2table(NaN);
end
end
end
7 Kommentare
Subhadeep Koley
am 12 Feb. 2020
Your "dataset.csv" is encoded with UTF-16-LE, which is not fully supported by the function readtable. Therefore, I copied and pasted all the data in a new .xlsx file (attached here).
The below code might be helpful now although it is not a very efficient solution.
clc;
data = readtable('Book1.xlsx');
[rows, cols] = size(data);
newData = data;
for i = 1: rows
for j = 1: cols
temp = table2array(data(i, j));
if iscell(temp)
temp = cell2mat(temp);
end
if temp == -9
newData(i, j) = array2table(NaN);
end
end
end
Steven Lord
am 12 Feb. 2020
The standardizeMissing function can accept arrays of various types, including table arrays and timetable arrays. If you only want to standardize the form in which missing data is stored for certain variables in your table you can tell it to only operate on specific 'DataVariables' as well.
0 Kommentare
BN
am 12 Feb. 2020
Bearbeitet: BN
am 12 Feb. 2020
I think you won't need to use for loop. If A is the name of the table, then you can just use:
A= readtable('dataset.csv');
A{:,:}(A{:,:}==-9) = NaN
9 Kommentare
BN
am 12 Feb. 2020
Oh yes I'm sorry I had a typo, use this:
A= readtable('dataset.csv');
A2 = table2array(A);
A2(A2==-9) = NaN;
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